🌍 Data Analyst using spatial data to drive business decisions
I'm a Geospatial Data Analyst with 6+ years of experience developing data-driven solutions using Remote Sensing, Earth Observation, GIS, and Spatial Analytics for environmental monitoring and infrastructure projects.
I work with Python, SQL, ArcGIS, QGIS, Google Earth Engine, and Machine Learning to process, analyze, and automate large geospatial datasets, transforming satellite imagery into actionable insights for environmental and operational decision-making.
| Repository | Description | Tech |
|---|---|---|
| geo-dengue-niteroi | End-to-end GIS case study covering data cleaning, spatial analysis, dengue incidence calculation, and interactive web mapping. | R • Leaflet • HTML |
| data-analyst-portfolio(In Progress) | Portfolio of data analytics projects covering Python, SQL, statistics, visualization and machine learning. | Python • SQL • Snowflake |
| Rayshader-RJ | High-quality 3D terrain visualization using R and the rayshader package. | R |
| INPE_Disciplinas | Python notebooks developed during my M.Sc. in Remote Sensing at INPE. (Portuguese) | Python • Jupyter |
| PythonParaGeociencias | Teaching materials for an introductory Python course for Geosciences. (Portuguese) | Python • Jupyter |
| Mapeamento-Costeiro-R | Coastal mapping course materials developed at Universidade Federal Fluminense. (Portuguese) | R |
| GeoPython_Materials | Curated collection of Python geospatial packages, references, and learning resources. | Python |
- Automated geospatial processing pipelines for 200,000+ address records, reducing manual work by ~80% using Python, SQL, and ArcGIS.
- Developed machine learning workflows for Land Use/Land Cover classification using Sentinel-2, CBERS-4A, and multi-source Earth Observation datasets.
- Built scalable and reproducible geospatial analytics workflows using Python, R, Git, Google Earth Engine, and Brazil Data Cube.
- Supported enterprise GIS operations across six regional business units, improving automation, data quality, and spatial decision support.
- Spatial Data Analytics
- Remote Sensing & Earth Observation
- Python (GeoPandas, Rasterio, GDAL)
- SQL & Spatial SQL
- Google Earth Engine
- Machine Learning for Geospatial Data
- Geospatial Data Processing
- Spatial Statistics & Spatial Analysis
- Raster & Vector Processing
- Workflow Automation
- QA/QC
- ArcGIS Pro | ArcGIS Enterprise | QGIS
- Web GIS
- Coordinate Reference Systems (CRS)
- PostGIS
- Cloud Computing (AWS & GCP)
- Geospatial APIs & Data Engineering
- Snowflake
- Docker
- French 🇫🇷